We will develop a spatially explicit simulation model that will predict the temporal and spatial distribution of West Nile virus (WNV) in multi-host and multi-vector systems. To achieve this goal, data from existing sources, proposed experiments, and proposed observations will be used to set the types of interactions and place realistic limits on the parameters of the model. Additionally, we have identified a system that will be useful as a surveillance system for amplification dynamics of WNV and human health risk. Nesting cliff swallows and house sparrows that opportunistically use cliff swallow colonies are in intimate contact with cimicid swallow bugs early in the spring of each year. We have pilot data to show that both bugs and swallows become infected with WNV. If the bugs maintain viable virus over winter then there is an opportunity to infect avian hosts quickly and efficiently the following spring. This in turn would allow for the rapid establishment of areas of high intensity of infection. Mosquitoes that feed on nestlings and adults are then more likely to become infected relative to the populations away from swallow colonies and riparian areas. Because mosquitoes can travel up to several miles from the site where they acquired the infection, they represent a source of infection to the general avian population and other incidental hosts. Our experiments are designed to test the assertion that swallow bugs are a source of early season infection and the spatial pattern to WNV prevalence in mosquito populations near and at some distance from cliff swallow colonies. Other studies by this group, but not part of this funding proposal, are designed to monitor infection rates of the general avian community away from cliff swallow sites. Finally, because we will be sampling areas inside and outside mosquito control districts we will be able to asses whether existing vector (mosquito) control programs are effective at decreasing the amplification potential and intensity of WNV infection of hosts and vectors. This study will provide both a risk management simulation model and empirical surveillance system.